-i - ignore errors
-c - continue
-t - use video title as file name
--extract-audio - extract audio track
| . | |
| .. | |
| ........ | |
| @ | |
| * | |
| *.* | |
| *.*.* | |
| 🎠|
| domain,ttl,aaaa-ttl,cname-ttl,miltiple-ttls,ns-root,ns-ttl,a-count,aaaa-count,a-records,aaaa-records,ns-records,cname | |
| facebook.com,300,300,,false,facebook.com,128517,1,1,"31.13.66.36","2a03:2880:f113:83:face:b00c:0:25de","a.ns.facebook.com.,b.ns.facebook.com.", | |
| twitter.com,300,,,false,dynect.net,42239,4,0,"199.16.156.102,199.16.156.198,199.16.156.70,199.16.156.230","","ns1.p34.dynect.net.,ns3.p34.dynect.net.,ns4.p34.dynect.net.,ns2.p34.dynect.net.", | |
| google.com,300,300,,false,google.com,128501,1,1,"216.58.209.14","2a00:1450:4017:803:0:0:0:200e","ns3.google.com.,ns4.google.com.,ns1.google.com.,ns2.google.com.", | |
| youtube.com,300,300,,false,google.com,128505,1,1,"216.58.209.206","2a00:1450:4017:803:0:0:0:200e","ns3.google.com.,ns4.google.com.,ns1.google.com.,ns2.google.com.", | |
| wordpress.org,600,,,false,wordpress.org,54943,2,0,"66.155.40.249,66.155.40.250","","ns4.wordpress.org.,ns3.wordpress.org.,ns1.wordpress.org.,ns2.wordpress.org.", | |
| linkedin.com,300,300,,false,dynect.net,47775,1,1,"108.174.10.10","2620:109:c002: |
| #!/usr/bin/python | |
| import re | |
| import os | |
| import sys | |
| import socket | |
| import threading | |
| from time import sleep | |
| from pwn import * |
| #!/usr/bin/env python3 | |
| # toy RSA key generation/encryption/decryption | |
| # this is only a demonstration of the underlying math - extremely unsafe! | |
| # unmodified textbook RSA is both malleable and semantically insecure. | |
| import subprocess | |
| from gmpy import invert # requires gmpy for modular inversion | |
| def ascii2int(string): # function for converting an ascii string to a single integer so that we can do math on it |
| #!/usr/bin/python | |
| import sys | |
| from keystone import * | |
| from unicorn import * | |
| from unicorn.arm_const import * | |
| from capstone import * | |
| from capstone.arm import * | |
| from capstone.x86 import * |
| #!/bin/bash | |
| #no PATH, no way to accidently run any programs | |
| PATH='' | |
| #useful variables | |
| term_height=0 | |
| term_width=0 | |
| term_scroll_height=0 | |
| status_line_row=0 |
The following is some nba articles fully-automatically generated by char-cnn, a recurrent-neural-network library thanks to Andrej Karpathy [link]. The library is awesome to easy, and very user-friendly. You should try it! :)
Basically, I wrote a python script [link] to extract past archives . And use that as the training set for the recurrent neural network.
The articles below are generated by a network trained with rougly about 2 millions character (which is an okay size; not big enough though). You can see that the generated article contains artificial author names, speeches, etc; similar to an nba archive (although the logic has to be improved, it is FUN.)
You can tune the parameter and train with a even bigger dataset using my script. And you will probably get better result! Have fun:)
| ffmpeg -i input_file.mp4 -vf scale=320:-1:flags=lanczos,fps=30 frames/ffout%03d.png | |
| convert -loop 0 frames/ffout*.png output_file.gif |